Professional Certificate in
Life Science Analytics
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The Life Science Analytics market size is predicted to reach USD 42.0 billion by 2025 from USD 22.1 billion in 2020 globally. Life Science Analysts are looking toward Big Data to adopt analytics for improving clinical trials and data standardization and for improved patient outcomes.
Overview of Life Science Analytics Course
Life Science Analytics uses various predictive and analytic tools to process Clinical Data Analysis, Genomic Sequencing, Pharmaceutical Trial Analysis, Patient Diagnosis Analysis, Disease Tracking and Modeling, Patient Treatment Personalization, Optimizing Analysis of Medical Documents etc.. for improved patient care. Huge databases are created based on past reports of patients that help in predicting the future trends of treatment for doctors as well as pharmaceutical companies.
Life Sciences is a vital part of future medication. Evidence-based medication is growing and it can help in the development of new drugs for medication. Analytics in the life science domain heightens the probability of better treatment and medication.
Life Science Analytics Course Training Learning Outcomes
Life Science Analytics has become a game-changer in the health industry. The Certification Program in Life Science Analytics Course is a sui generis attempt to blend analytics solutions for better medical treatment and the development of new drugs. Specifically designed to suit the Life Science professionals and data professionals who wish to understand the application of Big Data Analytics, Machine Learning, Neural Networks, and Deep Learning to Life Science industry data. Our Life Science Analytics course is meant for professionals from the finance domain as it provides a comprehensive picture of how data science and artificial intelligence can be leveraged to increase the efficiency of drugs and clinical trials. Understanding the applications of Data Science, Machine Learning to Life Sciences will be the prime objective of this content-rich program. Having a deep appreciation for Life Science Analytics is imperative for the success of various clinical trials and drug development.
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Who Should Sign Up?
- IT Engineers
- Data and Analytics Manager
- Business Analysts
- Data Engineers
- Math, Science Graduates
- Graduates Planning to Apply for Railway Jobs
Life Science Analytics Course Modules
The digital world is built on the walls of data and Life Sciences Analytics course is peering into the future. Put simply, Life Sciences Analytics is bringing in all the data and combining it to provide strategic as well as predictive insights that can be used to improve one’s business strategy. In this module on Life Sciences Analytics course, you will learn about the various systems and models of Life Sciences Analytics course and how Machine Learning is helping to improve life science research and improve patient care. You will learn about the various techniques used during the research and analyzing biological data. This module also throws light on the performance a life science project and can also be used in predicting patient disease diagnosis. You will also learn how Deep Learning is mining the genetic data, which is becoming pivotal in recognizing the heridetary diseases. Along with the various advanced Life Sciences Analytics techniques, you will also learn regarding Data Privacy and Security.
- Challenges in Life Sciences Analytics
- Life Sciences Analytics Market
- Life Sciences Analytics and Genetic Data
- Applications and Usecases
- Stages of Life Sciences Analytics
- Data Mining in Life Sciences Analytics
- EDA in Life Sciences Analytics
- Data Preprocessing in Life Sciences Analytics
- Data Mining in Genomics and Proteomics
- Feature Selection for a Genomic and Proteomic Studies
- K-means Clustering in Life Sciences Analytics
- K-means Clustering in Species Classification
- K-Nearest Neighbours in Life Sciences Analytics
- K-Nearest Neighbours in Genetic Algorithm
- Decision Tree Model in Life Sciences Analytics
- Decision Tree in Drug Classification
- Logistic Regression Model in Life Sciences Analytics
- Logistic Regression in Disease Tracking and Modeling
- Multi-Layer Perceptron Model in Life Sciences Analytics
- Multi-Layer Perceptron in Patient Diagnosis and Disease Prediction Analysis
Trends in Life Science Analytics Course
Understanding the potential of Life Science Analytics in todays market many corporate giants are coming forward to invest and process data.
- SENSIGHT, in September 2021 collected data through Sensyne’s research and developed an extensive database with NHS and US Health Systems that covers more than 22.5 million patients across wide range of diseases. The data analytics platform developed includes integrated easy to use algorithms that are used in research. This research algorithm will be able to research diseases, analytical tools and patient data from a decade back.
- In a recent development Solaris Biotechnology was acquired by Donaldson Co Inc. a pioneer in designing and bioprocessing equipment. With the equipment new tools and technology will be developed in Life Science sector.
- Bayer AG in April 2022 invested 1.3 billion euros to develop solutions for patients in areas with high medical need.
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